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Search indexed NASA NTRS and DOE OSTI research on propulsion, heat transfer, battery materials and energy systems. Follow report and document links to the original sources.

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At least 109 records · Page 6
All sourcesNASA NTRSDOE OSTI
NASA NTRS2000

Experimental Verification of Electric Drive Technologies Based on Artificial Intelligence Tools

In this report, a fully integrated prototype of a flight servo control system is successfully developed and implemented using brushless dc motors. The control system is developed by the fuzzy logic theory, and implemented with a multilayer neural network. First, a neural network-based architecture is introduced for fuzzy logic control. The characteristic rules and their membership functions of fuzzy systems are represented as the processing nodes in the neural network structure. The network structure and the parameter learning are performed simultaneously and online in the fuzzy-neural network system. The structure learning is based on the partition of input space. The parameter learning is based on the supervised gradient decent method, using a delta adaptation law. Using experimental setup, the performance of the proposed control system is evaluated under various operating conditions. Test results are presented and discussed in the report. The proposed learning control system has several advantages, namely, simple structure and learning capability, robustness and high tracking performance and few nodes at hidden layers. In comparison with the PI controller, the proposed fuzzy-neural network system can yield a better dynamic performance with shorter settling time, and without overshoot. Experimental results have shown that the proposed control system is adaptive and robust in responding to a wide range of operating conditions. In summary, the goal of this study is to design and implement-advanced servosystems to actuate control surfaces for flight vehicles, namely, aircraft and helicopters, missiles and interceptors, and mini- and micro-air vehicles.

Rubaai, Ahmed↗
NASA NTRS2001

High Power MPD Thruster Development at the NASA Glenn Research Center

Propulsion requirements for large platform orbit raising, cargo and piloted planetary missions, and robotic deep space exploration have rekindled interest in the development and deployment of high power electromagnetic thrusters. Magnetoplasmadynamic (MPD) thrusters can effectively process megawatts of power over a broad range of specific impulse values to meet these diverse in-space propulsion requirements. As NASA's lead center for electric propulsion, the Glenn Research Center has established an MW-class pulsed thruster test facility and is refurbishing a high-power steady-state facility to design, build, and test efficient gas-fed MPD thrusters. A complimentary numerical modeling effort based on the robust MACH2 code provides a well-balanced program of numerical analysis and experimental validation leading to improved high power MPD thruster performance. This paper reviews the current and planned experimental facilities and numerical modeling capabilities at the Glenn Research Center and outlines program plans for the development of new, efficient high power MPD thrusters.

LaPointe, Michael R.↗
NASA NTRS2003

Design Considerations of ISTAR Hydrocarbon Fueled Combustor Operating in Air Augmented Rocket, Ramjet and Scramjet Modes

The development and ground test of a rocket-based combined cycle (RBCC) propulsion system is being conducted as part of the NASA Marshall Space Flight Center (MSFC) Integrated System Test of an Airbreathing Rocket (ISTAR) program. The eventual flight vehicle (X-43B) is designed to support an air-launched self-powered Mach 0.7 to 7.0 demonstration of an RBCC engine through all of its airbreathing propulsion modes - air augmented rocket (AAR), ramjet (RJ), and scramjet (SJ). Through the use of analytical tools, numerical simulations, and experimental tests the ISTAR program is developing and validating a hydrocarbon-fueled RBCC combustor design methodology. This methodology will then be used to design an integrated RBCC propulsion system that produces robust ignition and combustion stability characteristics while maximizing combustion efficiency and minimizing drag losses. First order analytical and numerical methods used to design hydrocarbon-fueled combustors are discussed with emphasis on the methods and determination of requirements necessary to establish engine operability and performance characteristics.

Andreadis, Dean↗
NASA NTRS2002

Design Considerations of Istar Hydrocarbon Fueled Combustor Operating in Air Augmented Rocket, Ramjet and Scramjet Modes

The development and ground test of a rocket-based combined cycle (RBCC) propulsion system is being conducted as part of the NASA Marshall Space Flight Center (MSFC) Integrated System Test of an Airbreathing Rocket (ISTAR) program. The eventual flight vehicle (X-43B) is designed to support an air-launched self-powered Mach 0.7 to 7.0 demonstration of an RBCC engine through all of its airbreathing propulsion modes - air augmented rocket (AAR), ramjet (RJ), and scramjet (SJ). Through the use of analytical tools, numerical simulations, and experimental tests the ISTAR program is developing and validating a hydrocarbon-fueled RBCC combustor design methodology. This methodology will then be used to design an integrated RBCC propulsion system thai: produces robust ignition and combustion stability characteristics while maximizing combustion efficiency and minimizing drag losses. First order analytical and numerical methods used to design hydrocarbon-fueled combustors are discussed with emphasis on the methods and determination of requirements necessary to establish engine operability and performance characteristics.

Andreadis, Dean↗
DOE OSTI2024

From Chaos to Clarity: Autonomous Materials Discovery for Extreme Environments [Slides]

The pursuit of advanced functional materials for energy applications demands an understanding of their behavior under the most challenging conditions. Extreme environments, characterized by intense radiation, high temperatures, and corrosive chemistries, push materials to their limits, often revealing unexpected behaviors and degradation pathways. Traditional materials research approaches, relying on trial-and-error experimentation, are often slow and resource-intensive, ill-suited to the complexities of extreme environments. This talk will explore the transformative potential of autonomous materials science in revolutionizing our understanding of materials synthesis and degradation in extreme environments. By integrating advanced microscopy techniques, artificial intelligence, and robotic experimentation, we can accelerate the discovery and design of resilient materials for a sustainable future. The presentation will highlight recent breakthroughs in autonomous microscopy, computer vision, and machine learning, showcasing their ability to unravel complex material transformations at the atomic scale. The talk will also delve into the challenges and opportunities associated with deploying autonomous systems to probe extreme environments, emphasizing the importance of robust algorithms, real-time data analysis, and adaptive experimentation. The ultimate goal is to empower scientists with unprecedented capabilities to explore, understand, and engineer materials that can withstand the harshest conditions, paving the way for innovations in energy, aerospace, and beyond.

14 SOLAR ENERGY↗
DOE OSTI2024

From Chaos to Clarity: Autonomous Materials Discovery for Extreme Environments

The pursuit of advanced functional materials for energy applications demands an understanding of their behavior under the most challenging conditions. Extreme environments, characterized by intense radiation, high temperatures, and corrosive chemistries, push materials to their limits, often revealing unexpected behaviors and degradation pathways. Traditional materials research approaches, relying on trial-and-error experimentation, are often slow and resource-intensive, ill-suited to the complexities of extreme environments. This talk will explore the transformative potential of autonomous materials science in revolutionizing our understanding of materials synthesis and degradation in extreme environments. By integrating advanced microscopy techniques, artificial intelligence, and robotic experimentation, we can accelerate the discovery and design of resilient materials for a sustainable future. The presentation will highlight recent breakthroughs in autonomous microscopy, computer vision, and machine learning, showcasing their ability to unravel complex material transformations at the atomic scale. The talk will also delve into the challenges and opportunities associated with deploying autonomous systems to probe extreme environments, emphasizing the importance of robust algorithms, real-time data analysis, and adaptive experimentation. Our ultimate goal is to empower scientists with unprecedented capabilities to explore, understand, and engineer materials that can withstand the harshest conditions, paving the way for innovations in energy, aerospace, and beyond.

artificial intelligence↗
DOE OSTI2027

Conceptual design of highly-constrained splitters for the FFA@CEBAF energy upgrade study

The Continuous Electron Beam Accelerator Facility (CEBAF) at Jefferson Lab is investigating a significant energy upgrade utilizing Fixed-Field Alternating-gradient (FFA) recirculating arcs. This upgrade requires the design of complex horizontal beam splitters to manage up to six concurrent beam passes. This paper presents the conceptual design of these splitters, which are subject to severe physical constraints imposed by the existing accelerator tunnel and multifaceted beam dynamics requirements for matching into the permanent-magnet FFA arcs. The design methodology, centered on multi-pass simulations in the Bmad toolkit, is detailed from the initial geometric layout through the advanced optics matching. Key results include a robust geometric arrangement that fits within the spatial boundaries and the development of multiple, flexible optics matching solutions. Furthermore, the design integrates a viable scheme for extracting high-energy beams for the experimental halls, a critical operational requirement. This work establishes a comprehensive and viable conceptual design, forming a baseline for future engineering and performance optimization studies.

Bodenstein, R.M. [Thomas Jefferson National Accele↗
NASA NTRS2001

National Transonic Facility Wall Pressure Calibration Using Modern Design of Experiments (Invited)

The Modern Design of Experiments (MDOE) has been applied to wind tunnel testing at NASA Langley Research Center for several years. At Langley, MDOE has proven to be a useful and robust approach to aerodynamic testing that yields significant reductions in the cost and duration of experiments while still providing for the highest quality research results. This paper extends its application to include empty tunnel wall pressure calibrations. These calibrations are performed in support of wall interference corrections. This paper will present the experimental objectives, and the theoretical design process. To validate the tunnel-empty-calibration experiment design, preliminary response surface models calculated from previously acquired data are also presented. Finally, lessons learned and future wall interference applications of MDOE are discussed.

Underwood, Pamela J.↗
DOE OSTI2024

Qudit Gate Decomposition Dependence for Lattice Gauge Theories

In this work, we investigate the effect of decomposition basis on primitive qudit gates on superconducting radio-frequency cavity-based quantum computers with applications to lattice gauge theory. Three approaches are tested: SNAP & Displacement gates, ECD & single-qubit rotations $R(\theta,\phi)$, and optimal pulse control. For all three decompositions, implementing the necessary sequence of rotations concurrently rather then sequentially can reduce the primitive gate run time. The number of blocks required for the faster ECD &$R_p(\theta)$ is found to scale $\mathcal{O}(d^2)$, while slower SNAP & Displacement set scales at worst $\mathcal{O}(d)$. For qudits with $d<10$, the resulting gate times for the decompositions is similar, but strongly-dependent on experimental design choices. Optimal control can outperforms both decompositions for small $d$ by a factor of 2-12 at the cost of higher classical resources. Lastly, we find that SNAP & Displacement are slightly more robust to a simplified noise model.

Kürkçüoglu, Doga Murat↗
NASA NTRS2019

Challenges in Qualification of Thermal Protection Systems in Extreme Entry Environments

Planetary entry vehicles employ ablative TPS materials to shield the aeroshell from entry aeroheating environments. To ensure mission success, it must be demonstrated that the heat shield system, including local features such as seams, does not fail at conditions that are suitably margined beyond those expected in flight. Furthermore, its thermal response must be predictable, with acceptable fidelity, by computational tools used in heat shield design. Mission assurance is accomplished through a combination of ground testing and material response modelling. A material's robustness to failure is verified through arcjet testing while its thermal response is predicted by analytical tools that are verified against experimental data. Due to limitations in flight-like ground testing capability and lack of validated high-fidelity computational models, qualification of heat shield materials is often achieved by piecing together evidence from multiple ground tests and analytical simulations, none of which fully bound the flight conditions and vehicle configuration. Extreme heating environments (>2000 W/sq. cm heat flux and >2 atm pressure), experienced during entries at Venus, Saturn and Ice Giants, further stretch the current testing and modelling capabilities for applicable TPS materials. Fully-dense Carbon Phenolic was the material of choice for these applications; however, since heritage raw materials are no longer available, future uses of re-created Carbon Phenolic will require re-qualification. To address this sustainability challenge, NASA is developing a new dual-layer material based on 3D weaving technology called Heat shield for Extreme Entry Environments (HEEET). Regardless of TPS material, extreme environments pose additional certification challenges beyond what has been typical in recent NASA missions. Scope of this presentation: This presentation will give an overview of challenges faced in verifying TPS performance at extreme heating conditions. Examples include: (1) Bounding aeroheating parameters (heat flux, pressure, shear and enthalpy) in ground facilities. How to certify TPS if environments can't be bounded or aeroheating parameters can't be simultaneously achieved. (2) Higher uncertainties in ground test environments (facility calibration and analytical predictions) at extreme conditions. (3) Testing in flows similar to planetary atmosphere composition (H2/He for Gas and Ice Giants). (4) Test sample size limitations for qualifying seam designs. (5) Lack of computational tools capable of simulating all significant aspects of TPS performance (including initiation and propagation of failures). This presentation will provide recommendations on how the EDL community can address these challenges and mitigate some of the risks involved in flying TPS materials at extreme conditions. Examples include: (1) Dedicated activity to understanding TPS failure modes. Develop computational tools capable of modelling fluid interaction with material's thermostructural response. Validate these tools through failure testing. A better understanding of failure mechanisms may eliminate the need to fully bound all aeroheating parameters in ground testing. (2) Enhancements to current testing facilities to simulate flight-like ablation mechanism (ex. testing in Nitrogen at Ames Interaction Heating Facility to limit oxidation in favor of more sublimation). (3) Improved characterization of test conditions with new diagnostic methods and determination of environment uncertainty through rigorous statistical analysis of available data. (4) Design margin policies that are directly tied to uncertainties in ground test environments and modelling fidelity

Mahzari, Milad↗
NASA NTRS1996

Magnetic Leviation System Design and Implementation for Wind Tunnel Application

This paper presents recent work in magnetic suspension wind tunnel development in National Cheng Kung University. In this phase of research, a control-based study is emphasized to implement a robust control system into the experimental system under study. A ten-coil 10 cm x 10 cm magnetic suspension wind tunnel is built using a set of quadrant detectors for six degree of freedom control. To achieve the attitude control of suspended model with different attitudes, a spacial electromagnetic field simulation using OPERA 3D is studied. A successful test for six degree of freedom control is demonstrated in this paper.

Lin, Chin E.↗
NASA NTRS2001

Experimental Investigation of Local Oscillator Chains with GaAs Planar Diodes at Cryogenic Temperatures

This paper will describe a robust test-bed that has been built to measure multiplier performance over a wide range of temperatures and frequencies. In a 182-212 GRz designed balanced doubler the peak efficiency at 201 GHz improves from 22% to 28% upon cooling from 300 K to 120 K. This stage is then used to pump a 362-424 GRz balanced planar doubler. The peak chain efficiency increases from 3.4% to 6% when the two cascaded doublers are cooled from 300 K to 120 K. This enables the production of 10 mW of peak output power at 377 GHz, which ought to be sufficient for driving the next stage multiplier.

Maestrini, A.↗
DOE OSTI2025

Exploring single-cell biosynthetic noise and dynamics for enhanced betaxanthin production in Escherichia coli

Cell-to-cell variability often limits the efficiency of microbial bioproduction, yet how individual cells fluctuate over time and how these fluctuations shape population-level output remain unclear. To address this issue, we tracked a heterologous betaxanthin pathway in Escherichia coli using microfluidics-assisted time-lapse microscopy, allowing simultaneous measurement of fluctuations in betaxanthin, its biosynthetic enzyme DOD and growth across generations. Here we show that over 50% of high betaxanthin producers become medium or low producers after two divisions. Betaxanthin variation primarily originates from DOD noise, with a smaller contribution from growth rate fluctuations. We further develop a stochastic model to explore various control circuits and find that pathway enzyme or metabolite-based growth selection strategies are most effective in enhancing production. We experimentally validate the model by coupling enzyme expression to nutrient availability, which enriches high producers and boosts titer by 4.4-fold. Our results highlight key sources of metabolic heterogeneity and provide a framework for designing robust microbial processes.

Bacterial systems biology↗
DOE OSTI2024

Dual-Band Polarization Control with Pairwise Positioning of Polarization Singularities in Metasurfaces

Emerging applications of metasurfaces in classical and quantum optics are driving the need for precise polarization control of nearly-degenerate, high quality (𝑄)-factor modes. However, current approaches to creating specifically polarized pairs of modes force a trade-off between maintaining high 𝑄 factors and robustness. Here, we solve this challenge by employing pairwise generation, annihilation, and positioning of polarization singularities, derived from symmetry-guaranteed pairs of symmetry-protected bound states in the continuum. We experimentally demonstrate this design paradigm in silicon metasurfaces with mode splittings of ≈ 20 nm, mode splitting deviations as low as 1 nm, and 𝑄 factors up to 200. Furthermore, this approach opens new avenues for enhancing metasurface performance across a diverse range of applications, including sensing, modulating, nonlinear mixing, and generating quantum light.

Metasurfaces↗
NASA NTRS2024

Ejecta Management in a Safe Lithium Ion Battery Design

As lithium-ion battery energy densities continue to rise, managing the heat and pressure generated during failure events has become increasingly critical. Safety systems must effectively relieve pressure without releasing sparks, flames, or particulate matter, requiring robust filtration solutions. The challenge is compounded by the reduced free volume available for gas expansion in high-density designs, which increases the demands on these filters. While significant progress has been made through experimental studies and modeling efforts to understand the behavior of ejecta during battery failures, there remains a pressing need for practical, rule-of-thumb sizing parameters. These parameters would help correlate high-energy waste streams with appropriate filter design, ensuring reliable containment and safety. This talk will explore recent experimental findings in this area and discuss the potential pathways for developing these essential sizing guidelines.

Ejecta Management↗
NASA NTRS2000

Global Design Optimization for Aerodynamics and Rocket Propulsion Components

Modern computational and experimental tools for aerodynamics and propulsion applications have matured to a stage where they can provide substantial insight into engineering processes involving fluid flows, and can be fruitfully utilized to help improve the design of practical devices. In particular, rapid and continuous development in aerospace engineering demands that new design concepts be regularly proposed to meet goals for increased performance, robustness and safety while concurrently decreasing cost. To date, the majority of the effort in design optimization of fluid dynamics has relied on gradient-based search algorithms. Global optimization methods can utilize the information collected from various sources and by different tools. These methods offer multi-criterion optimization, handle the existence of multiple design points and trade-offs via insight into the entire design space, can easily perform tasks in parallel, and are often effective in filtering the noise intrinsic to numerical and experimental data. However, a successful application of the global optimization method needs to address issues related to data requirements with an increase in the number of design variables, and methods for predicting the model performance. In this article, we review recent progress made in establishing suitable global optimization techniques employing neural network and polynomial-based response surface methodologies. Issues addressed include techniques for construction of the response surface, design of experiment techniques for supplying information in an economical manner, optimization procedures and multi-level techniques, and assessment of relative performance between polynomials and neural networks. Examples drawn from wing aerodynamics, turbulent diffuser flows, gas-gas injectors, and supersonic turbines are employed to help demonstrate the issues involved in an engineering design context. Both the usefulness of the existing knowledge to aid current design practices and the need for future research are identified.

Shyy, Wei↗
DOE OSTI2026

Design and Performance Assessment of Intermediary Coils for Misalignment Tolerance Improvement in Wireless Power Transfer Systems

This paper investigates the use of intermediate coils positioned between the primary and secondary coils in Wireless Power Transfer (WPT) systems for electric vehicle (EV) charging, with the objective of improving power transfer efficiency and robustness under misalignment conditions. An optimized 1 kW power system that operates at 85 kHz is developed and the misalignment performance was analyzed and compared with and without intermediate coils. A preliminary increase in efficiency of 2.3% at a misalignment of 52% of the coil radius is shown to be possible for a passive intermediate coil. An experimental prototype is built for design verification.

Sivka, Gozde [ORNL]↗
DOE OSTI2026

Design Principles for the Synthesis of Self-Pillared ZSM-5 Zeolite Nanosheets

The design of next-generation materials for emerging energy and environmental applications heavily relies on empirical approaches to direct nonclassical nucleation and crystal growth pathways, polymorphism, intercrystalline transformations, and seed-assisted growth processes. A long-standing obstacle to nanoporous materials design is the complexity of their crystallization, which hinders the development of predictive models and/or physical descriptors that can guide their synthesis. In this study, we use a combination of state-of-the-art synthesis, characterization, and computational design to prepare hierarchical MFI-type zeolites, which we couple with benchmark catalytic testing to assess structure-property-performance relationships. These hierarchical materials are intergrowths of two commercially relevant zeolite frameworks, MFI and MEL, prepared as self-pillared pentasil (SPP) zeolites through seed-assisted, organic-free syntheses for which little theoretical guidance existed. Here, by comparing a large library of zeolite seeds with different pore sizes, dimensions, and structural composite building units, we determined the relative impact of seed and silica source selection, among other synthesis variables. Combined experimental and computational studies are used to test several hypotheses in literature to rationalize the choice of seed structure and establish a more robust selection criteria for seed-assisted synthesis of zeolites. Specifically, we show that a data-driven approach to develop structural descriptors correlates to new, facile routes to rationally design SPP zeolites, addressing knowledge gaps in the fundamental understanding of (non)classical crystal growth mechanisms that are characteristic of nanoporous aluminosilicates.

36 MATERIALS SCIENCE↗